Behind new dynamics of next generation of quant funds

It is probably something of an understatement to say that quant funds earned themselves a bad reputation during the global financial crisis.

In 2007 the Goldman Sachs Global Alpha fund is thought to have lost 40 per cent of its value after bets on currencies, equities and bonds went awry. Last year the investment bank closed the vehicle, which was established in 1997, after assets under management reportedly fell to less than $2 billion from $11 billion.

Former Wall Street Journal writer Scott Patterson wrote a book called The Quants: The Maths Geniuses Who Brought Down Wall Street. It tells the story of how quant-based proprietary trading desks at major investment banks, staffed by “young math whizzes” made their institutions fortunes in the boom years and then lost billions through the financial crash when their models couldn’t find a way out of the carnage.

Rather than looking at qualitative factors such as management style, sector trends and the competitive landscape, quant managers use sophisticated computer models to take bets on which assets will rise or fall in value. The beauty of the system is that it removes human emotion from investing.

But as markets gyrated wildly in 2007, 2008 and 2009, asset prices did not behave in the traditional manner and the models did not, or could not adjust.

It also emerged that many of the quant managers, using similar computer programs, were holding the same stocks and were forced towards the exit door at the same time. Some funds were leveraged, which only added to their woes.

The problem for many investors in these vehicles is that they assumed the funds were low risk.

“A lot of clients experienced poor performance in 2008 and 2009. The quant industry received a bit of a bad rap,” concedes Olivia Engel, Australian portfolio manager at State Street Global Advisers, which launched an Australian Dynamic Equity Fund, a quant strategy, earlier this year.

What the industry learned, the head of State Street’s global active equities team, Marc Reinganum says, was that a single trading model would not work across all environments. “There was not a deep enough appreciation that when you are not in a normal environment you need to respond in a systematic way,” he says.

“We realised we needed models that are more dynamic and responsive to the environment.”

The next generation systems, Reinganum says, gauge how investors react to the investment-related data and other trading information, which can then be used to predict the types of assets they will buy or sell next.

The data, or characteristics, that the computing systems analyse include sharemarket volatility, aggregate measures of share valuation, the price gap between high priced and low priced stocks, short term interest rates and credit spreads.

The computer models will put a greater or lesser emphasis on each piece of information, depending on the external environment.

“We look at what the broad market environment can tell us about which characteristics will come to the fore,” Engel says.

Before the global financial crisis, Engel says the quant models used to forecast long-term trends, but now the forecast horizon is often between three and six months.

The state of the globe at the end of 2011 is a convenient test case.

Towards the close of last year investor sentiment was in the dumps. Investors everywhere were anxious about the prospect that the European single currency would collapse. Markets were down and highly volatile, but analysis of sharemarkets in 2003 and 2009 found that in the months following a similar level of weakness, growth stocks began to shine.

“It is forecasting whether risk will be rewarded or penalised,” Reinganum says.

The State Street fund was switched into cyclicals such as miners, mining services companies, consumer discretionary and media stocks.

The trade was rewarded.

Cyclical stocks around the world have risen this year as investors have become more sanguine about the prospects for the global economy.

But six months later, Reinganum says, the pendulum has swung. Volatility has fallen and investors are expected to take a much more cautious approach.

As a result, the dynamic equity fund has been increasing its exposure to high-yielding property trusts, utilities and financials.

“We are not likely to see an explosive rally in the next three to six months, although we don’t expect the market to collapse,” Reinganum says. “The signals indicate a much more cautious approach is likely to be rewarded.”

Engel says she is very confident the dynamic fund would be able to withstand a financial crisis of similar magnitude to that seen in 2008.

“The way investors react to fear and crises and investment conditions is consistent,” she says.

The dynamic fund holds about 65 stocks. That said, State Street describes it as a “high conviction” vehicle – high conviction because it takes a bet on which sectors will outperform, and puts all its eggs in that basket.

The turnover of the fund can be as high as 100 per cent and 200 per cent a year.

This fund is anything but “buy and hold”.

But Engel argues there is room for ‘buy and hold’ strategies, as long as investors have the time to ride out severe and prolonged downturns, or are not concerned with performance over shorter time periods.

If they are approaching retirement, or are in retirement, they may not have the luxury of waiting.

“Buy and hold strategies can be relevant if investors’ horizons are very long term and they are not worried by relative performance,” Engel says. “But it can be too tempting for investors to give in to fear. We want to outperform in all stages of the investment cycle.”